construct.work_sample predicts construct.task_performance
normal · weakly_informative · 3 studies · N = 150
Distribution
Weakly informative prior. This prior is weakly informative. It will nudge your posterior but won't overwhelm it; expect data to do most of the work in modest samples.
Intervals
- Confidence interval (95%) — uncertainty about the mean ρ
- [0.19, 0.41]
- Credibility interval (95%) — distribution of the true effect across settings (the Bayesian prior)
- [0.30, 0.30]
- I² (heterogeneity) — share of total variance from between-study differences
- 0%
The true effect is ~constant across settings — it generalizes.
SD_ρ≈0 — true effect is ~constant across settings; generalizes (observed-score scale until artifact correction, PRN-058)
Evidence provenance
published ρ=0.30 (k=3, replication: meta-analytic); no primary-deployment evidence yet
| Source | ρ (r) | Scope |
|---|---|---|
| Published literature | 0.30 | k = 3 · N = 150 |
- replication: meta-analytic
- aging literature (freshness=0.37)
No primary-deployment evidence yet — this prior rests on published literature alone. As anonymized, aggregated effect sizes from real deployments are contributed, they appear here as a distinct, publication-bias-free source, fused with the literature into a posterior estimate.
Code
Drop this prior straight into your model. Snippets generated from the synthesized distribution + parameters.
target += normal_lpdf(beta | 0.314413, 0.0608581);beta = pm.Normal("beta", mu=0.314413, sigma=0.0608581)brms::prior(normal(0.314413, 0.0608581), class = "b")# base R sample
rnorm(N, mean = 0.314413, sd = 0.0608581)np.random.normal(loc=0.314413, scale=0.0608581, size=N)Parameters
| Family | Parameters |
|---|---|
| normal | I2 = 0.000, mu = 0.3144, sigma = 0.06086, r_mean = 0.3044, k_studies = 3.000, tau_squared = 0.000 |
Synthesis
- Method
- random_effects_meta
- Informativeness
- weakly_informative
- Replication status
- meta-analytic
- k_studies
- 3
- n_total
- 150
- Last updated
- 2026-05-30T22:53:22.352Z
Quality distribution
| Grade | Count |
|---|---|
| A | 2 |
| B | 1 |
| C | 0 |
| D | 0 |
Contributing effect sizes
Effect-size detail pages land with a later sub-ticket; for now, ids link to the filtered list. Browse all rows via /registry/effects.